For manufacturing industries, it is an important issue to decide actual control conditions (e.g., values, ranges, options, or the like) of various control factors (e.g., temperature, pressure, humidity, or the like) of a production line in order to improve yield related values (e.g., improve the yield and increase the yield rate). When there is a need in manufacturing new products, the manufacturers must set appropriate control conditions for the control factors of the production line. Moreover, during the process of manufacturing of the products, the manufacturers also need to timely evaluate whether the current control conditions of the control factors need to be adjusted. A production line usually involves multiple control factors, and various control conditions corresponding to the control factors form complicated control combinations, which makes the manufacturer hard to make a decision when setting the control conditions for the control factors.
Currently, many manufacturers rely on the experiences of the experienced practitioners for setting the control conditions of the control factors. This approach extremely depends on the experiences and does not evaluate the actual effect of each control factor on the yield related values of the production line objectively and comprehensively. Hence, the yield related values can only be improved after many times of adjustment. Some manufacturers design an experimental method (e.g., Taguchi method and response surface method) and obtain an optimal control condition set (including the control conditions of all the control factors) after many experiments. However, applying the optimal control condition set to an on-site production line is usually infeasible. For example, the control conditions that can be set for the control factors of an on-site production line are often restricted in range, variation amount, and/or adjustability. If the control condition(s) corresponding to some control factor(s) in the optimal control condition set cannot comply with the restriction, the optimal control condition set cannot be applied to the on-site production line.
In addition to the aforesaid drawbacks, when deciding/adjusting the control condition set to be adopted the production line, the conventional technology does not consider the cost and the benefits of adjusting the control factors and nor does it consider the burden on the production line if adjusting too many control factors at one time. Accordingly, it is an important task to efficiently decide and/or correct the control condition set (i.e., decide and/or correct the control conditions of the control factors) that can be actually applied to the production line and decide the adjustment order while taking all the aforesaid factors into consideration in order to improve the yield related values and gradually achieve the production target.